SHARE model for feasibility studies

Relying on proprietary models able to simulate the system operation on an hourly basis for the entire lifetime, DNV can offer accurate results.

• SHARE stands for Synergized Hydrogen and Renewables Estimator
• DNV's proprietary techno-economic optimisation model for green H₂ derivatives
• Can be used for green ammonia, e-methanol, green steel or any hydrogen derivative (e.g. SAF, HVO, etc.)
• Being programmed in Python, the model is robust and has a low computational time while it can be adjusted for each project situation
• With the objective to model the hourly optimal dispatch of the different assets (PV/wind/battery storage/H₂-storage/electrolyser/H₂-derivative process/grid imports) to optimize the levelized cost of green hydrogen and/or derivatives production

Our service

1. Techno-economic feasibility studies:
   The SHARE Model is a unique tool for conducting techno-economic feasibility studies. These are crucial in the early stages of project development as they assess whether a project is technically feasible and economically justifiable. The model helps in evaluating the technical aspects such as the technology to be used, the technical requirements of the project, and the technical risks involved. On the economic side, it aids in analyzing the projected costs, potential revenues, return on investment, and economic risks. By providing a comprehensive view of both the technical and economic aspects, the SHARE Model helps in making informed decisions about whether to proceed with a project.
   
   
2. Strengths of SHARE Model:
   • Techno-economic optimisation working in hourly basis and simulating the energy flows dispatch for the lifetime of a project while maintaining compliance with all technical constraints such as ramp rates/minimum load restrictions in upstream and downstream equipment around the electrolysis plant (for instance, ammonia or methanol plants, coexistence of electrolysis units with steam methane reformers, etc.)
   • The model can run many different scenarios or cases combining different capacities of the different systems to find the optimum sizing
   • The model has the flexibility to utilize various Wind/Solar capacities, along with multi-year profiles, and perform different degrees of interpolation based on available number of profiles
   • It simulates high resolution (hourly) input data, including hourly power price forecasts, making results far more realistic than existing assessments based on annual or monthly energy production data
   • It implements the regulatory restrictions associated to each geography. For instance, in EU based projects, the model includes the considerations required to produce an RFNBO according to the Delegated Act 27 to RED III
   • Enhanced Expandability: The model allows for seamless expansion by incorporating various modules that can leverage components from existing models. For example, the steam reforming module was specifically designed to be integrated into H₂-production in refineries, taking into consideration all relevant technical limitations. The same applies to Haber-Bosch and ASU units in ammonia production, or Synthesis and Distillation steps in Methanol production, with the intermediate storage equipment
   • Optimized Dispatch Strategy: By utilizing 72h-ahead forecasting for renewable power production and electricity prices, the model identifies the optimal dispatch strategy, enabling profitable arbitrage opportunities through storage utilization. Of course, the model adapts to any demand side profile in the supply of hydrogen or derivatives which is requested from the offtaker..

Our expertise

The SHARE model has been already used for hydrogen & derivative plants worldwide for a total installed capacity of electrolysis of more than 20 GW distributed in more than 40 projects.

But everything is not just about the application of SHARE model: our main added value is the expertise of the team in adjusting to the specifics of each project, the vast knowledge from our simulation experts in modelling green H₂ and derivative plants and the addition of technical experts for each asset in the value chain. This means realistic inputs for the modelling, so accurate figures on production and economic returns of the project from the early stages of development.